Darq Technologies

From Wikitia
Jump to navigation Jump to search

DARQ Technologies is an acronym for Distributed Ledger Technology (DLT), Artificial Intelligence (AI), Extended Reality (XR), and Quantum Mechanics (QM)[1]. These four emerging technologies in themeselves are at the technological forefront, and combined, they are expected to have a significant impact on multiple industries including: financial[2], health care[3], manufacturing, travel & tourism, management systems[4], information technology, and renewable energy[5].

Technologies

DARQ technologies represent a convergence of these four transformative technologies, offering synergies and new possibilities for innovation across various industries. Combining these technologies can unlock novel solutions, enhance security, improve efficiency, enable advanced problem-solving, and create immersive user experiences[2].

Core Technologies

Distributed Ledger Technology

Distributed Ledger Technology (DLT) refers to a database architecture that is distributed across multiple sites, countries, or institutions[6]. It operates as a decentralized system, where data is stored across a network of computers or nodes, rather than in a single central location, facilitating secure and transparent transactions without relying on intermediaries[7]. The foundation of DLT lies in cryptographic algorithms, which ensure the integrity and security of the stored data [6].

Distributed Ledger Technology (DLT) also serves as the foundation for creating digital assets, such as cryptocurrencies. Cryptocurrencies are digital or virtual tokens that utilize cryptographic techniques to ensure security and are built upon DLT[8]. These decentralized currencies function autonomously, operating without the involvement of central banks[7]. Well-known examples of cryptocurrencies include Cardano, Ethereum, Solana, Tron.

Artificial Intelligence

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. AI is a broad field that encompasses many different techniques and approaches, including machine learning, natural language processing, computer vision, and robotics.

The large language model (LLM), a deep learning model that possesses an extensive set of parameters, started to emerge around 2018 and since then have been used in a variety of fields, including natural language processing, healthcare[9][10], chemistry[11], academic research[12], and software development [13]. These models are trained using unsupervised methods on vast amounts of textual data[14].

Extended Reality

Extended Reality (XR) is a term used to describe a range of technologies that offer immersive and interactive experiences beyond what is possible with traditional screens or interfaces. These technologies include Virtual Reality (VR),Augmented Reality (AR), Mixed Reality (MR), and other related technologies.

One prominent application of XR is the metaverse which refers to a collective virtual shared space where users can interact with each other and digital objects in real-time, creating a new form of interconnected reality. It can be thought of as a massive, persistent, and dynamic virtual universe that exists parallel to the physical world[15].

Quantum Technology

Quantum Technology, prominently Quantum Computing (QC), is a type of technology that is based on the principles of Quantum mechanics, which describes the behavior of matter and energy at the atomic and subatomic level. Quantum technology leverages the unique properties of quantum systems, such as superposition and entanglement, to perform complex calculations and operations that are beyond the capabilities of classical computers.

Quantum cryptography and quantum key distribution are two emerging technologies that are expected to play a critical role in the coming future to mitigate vulnerabilities of traditional cryptographic methods in the face of quantum algorithms[16]

DARQ Technologies Combined

DLT AI

The convergence of Distributed Ledger Technology (DLT) and Artificial Intelligence (AI) is an area of active research and development. The combination of these two technologies has the potential to create new applications and services that are more secure, transparent, and efficient than traditional systems. DLT is impacted by AI focusing on AI-based consensus algorithms, smart contract security, selfish mining, decentralized coordination, DLT fairness, non-fungible tokens (NFT), decentralized finance, decentralized autonomous organizations (DAOs), and more[17].

Quantum AI

A Quantum Language Model (QLM) is a language model built using the principles of Quantum Probability Theory, which is a mathematical framework that describes the behavior of quantum systems. The QLM is a stochastic model that can take advantage of quantum correlations due to interference and entanglement. It is a new approach for building language models that has been explored in recent years by the Natural Language Processing (NLP) community. The QLM is a proof-of-concept study that aims to show the potential of this approach rather than building a complete application for solving language modeling problems for any setting[18].

Quantum natural language processing (QNLP) is the application of quantum computing to natural language processing (NLP) that takes the phenomenon of superposition, entanglement, interference to run NLP models or language related tasks on the hardware. It computes word embeddings as parameterised quantum circuits that can solve NLP tasks faster than any classical computer[19].

Quantum Many-body Wave Function (QMWF) inspired language modeling approach to address the limitations of existing quantum-inspired language models (QLMs) in modeling the interaction among words with multiple meanings and integrating with neural networks[20].

References

  1. ↑ "The post-digital era is upon us: Are you ready for what's next" (PDF). Accenture Technology Vision 2019. Retrieved February 22, 2021.
  2. ↑ 2.0 2.1 Gigante, G, Zago, A (2023). "DARQ technologies in the financial sector: artificial intelligence applications in personalized banking". Qualitative Research in Financial Markets. 15 (1): 29–57. doi:10.1108/QRFM-02-2021-0025.
  3. ↑ Miliard, M. (2021). "Accenture has a DARQ vision of healthcare's 'post-digital' era". Healthcare IT News.
  4. ↑ Kisielnicki, J.; Zadrożny, J. (2021). "DARQ technology as a digital transformation strategy in terms of global crises". Journal Name. 19 (3 (93)): 150–167.
  5. ↑ Manoharan, R. (2021). "The Applied Energy Systems Enacting the Ever Green Energy for our planet: Confluence of DARQ Technologies". SPAST Abstracts. 1 (01).
  6. ↑ 6.0 6.1 Gourisetti, Sri Nikhil Gupta; Cali, Ümit; et al. (2021). "Standardization of the Distributed Ledger Technology cybersecurity stack for power and energy applications". Sustainable Energy, Grids and Networks. 28: 100553. doi:10.1016/j.segan.2021.100553. ISSN 2352-4677.
  7. ↑ 7.0 7.1 Silva, E.C.; da Silva, M.M. (2022). "Research contributions and challenges in DLT-based cryptocurrency regulation: a systematic mapping study". Journal of Banking and Financial Technology. 6: 63–82.
  8. ↑ Ferreira, A.; Sandner, P. G.; Dünser, T. (2021). "Cryptocurrencies, DLT and Crypto Assets – the Road to Regulatory Recognition in Europe". Forthcoming in: Handbook on Blockchain. doi:10.2139/ssrn.3891401.
  9. ↑ Sallam, M. (2023). "ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns". Healthcare. 11 (6): 887. doi:10.3390/healthcare11060887.
  10. ↑ Cascella, M.; Montomoli, J.; Bellini, V. (2023). "Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios". J Med Syst. 47 (33). doi:10.1007/s10916-023-01925-4.
  11. ↑ White, A. D. (2023). "The future of chemistry is language". Nature Reviews Chemistry: 1–2.
  12. ↑ Rahman, Md. Mizanur; Terano, Harold Jan; Rahman, Md Nafizur; Salamzadeh, Aidin; Rahaman, Md. Saidur (2023). "ChatGPT and Academic Research: A Review and Recommendations Based on Practical Examples". Journal of Education, Management and Development Studies. 3 (1): 1–12. doi:10.52631/jemds.v3i1.175.
  13. ↑ Ross, Steven I.; Martinez, Fernando; Houde, Stephanie; Muller, Michael; Weisz, Justin D. (2023). "The programmer's assistant: Conversational interaction with a large language model for software development". ACM Conference on Intelligent User Interfaces (IUI).
  14. ↑ Birhane, A.; Kasirzadeh, A.; Leslie, D.; Wachter, S. (2023). "Science in the age of large language models". Nat. Rev. Phys. 5: 277–280.
  15. ↑ Ritterbusch, Georg David; Teichmann, Malte Rolf (2023). "Defining the Metaverse: A Systematic Literature Review". IEEE Access. 11: 12368–12377. doi:10.1109/ACCESS.2023.3241809. ISSN 2169-3536.
  16. ↑ Ahn, Jongmin, et al. (19 January 2022). "Toward Quantum Secured Distributed Energy Resources: Adoption of Post-Quantum Cryptography (PQC) and Quantum Key Distribution (QKD)". Energies. 15 (3): 714. doi:10.3390/en15030714.
  17. ↑ Bellagarda, J. S.; Abu-Mahfouz, A. M. (2022). "An updated survey on the convergence of distributed ledger technology and artificial intelligence: Current state major challenges and future direction". IEEE Access. 10: 50774–50793.
  18. ↑ Basile, Ivano; Tamburini, Fabio (September 7–11, 2017). "Towards Quantum Language Models". Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Copenhagen, Denmark. pp. 1840–1849.
  19. ↑ Ganguly, S.; Morapakula, S.N.; Coronado, L.M.P. (2022). "Quantum natural language processing based sentiment analysis using lambeq toolkit". 2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T). pp. 1–6.
  20. ↑ Zhang, Peng; Su, Zhan; Zhang, Lipeng; uWang, Benyo; Song, Dawei (Oct 2018). "A quantum many-body wavefunction inspired language modeling approach". Proceedings of the 27th ACM International Conference on Information and Knowledge Management.

External links

Add External links

This article "Darq Technologies" is from Wikipedia. The list of its authors can be seen in its historical. Articles taken from Draft Namespace on Wikipedia could be accessed on Wikipedia's Draft Namespace.

Retrieved from "https://wikitia.com/index.php?title=Darq_Technologies&oldid=180494"